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AI Research
arXiv CS.AI·Jun 12·5 min read
The Challenges of Balancing AI Compliance and Technological Innovations in Critical Sectors: A Systematic Literature Review
TL;DR
Critical sectors like healthcare and finance face challenges in integrating AI due to fragmented regulations and compliance burdens. A systematic literature review identified governance strategies such as risk-tiered regulation and explainable AI to address these issues.
✦ Why It Matters
Engineers can leverage governance strategies to ensure AI innovations comply with regulations while fostering development.
Key Takeaways
- Implement risk-tiered regulation to reduce compliance burdens.
- Adopt compliance by design in AI development processes.
- Utilize explainable AI to enhance transparency and trust.
- Engage with policymakers to align governance with innovation.
How It Works
The proposed governance strategies focus on integrating compliance into the AI development lifecycle. Risk-tiered regulation allows for differentiated compliance requirements based on the potential impact of AI applications, easing the burden on SMEs.
Compliance by design emphasizes embedding regulatory considerations into the design phase of AI systems, ensuring that they meet standards from the outset. Explainable AI enhances user trust by making AI decision-making processes transparent and understandable.